Conferences related to Algorithmic Game Theory

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2019 IEEE 58th Conference on Decision and Control (CDC)

The CDC is recognized as the premier scientific and engineering conference dedicated to the advancement of the theory and practice of systems and control. The CDC annually brings together an international community of researchers and practitioners in the field of automatic control to discuss new research results, perspectives on future developments, and innovative applications relevant to decision making, systems and control, and related areas.The 58th CDC will feature contributed and invited papers, as well as workshops and may include tutorial sessions.The IEEE CDC is hosted by the IEEE Control Systems Society (CSS) in cooperation with the Society for Industrial and Applied Mathematics (SIAM), the Institute for Operations Research and the Management Sciences (INFORMS), the Japanese Society for Instrument and Control Engineers (SICE), and the European Union Control Association (EUCA).


2019 International Conference on Robotics and Automation (ICRA)

Flagship conference of the robotics and automation society, a premiere international venue for international robotics researchers


ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

The 2019 IEEE International Conference on Communications (ICC) will be held from 20-24 May 2019 at Shanghai International Convention Center, China,conveniently located in the East Coast of China, the region home to many of the world’s largest ICT industries and research labs. Themed“Smart Communications”, this flagship conference of IEEE Communications Society will feature a comprehensive Technical Program including16 Symposia and a number of Tutorials and Workshops. IEEE ICC 2019 will also include an attractive Industry Forum & Exhibition Program featuringkeynote speakers, business and industry pan


IEEE INFOCOM 2019 - IEEE Conference on Computer Communications

IEEE INFOCOM solicits research papers describing significant and innovative research contributions to the field of computer and data communication networks. We invite submissions on a wide range of research topics, spanning both theoretical and systems research.


SoutheastCon 2019

The annual IEEE SoutheastCon conferences promote all aspects of theories and applications of engineering disciplines. Sponsored by the IEEE Region-3 and IEEE Huntsville Section, this event will attract researchers, professionals, and students from the Southeastern region of the U.S. SoutheastCon 2019 will feature tutorial sessions, workshops, Technical Programs, and student Hardware, Software, Ethics, Paper, Web competitions.

  • SoutheastCon 2018

    SoutheastCon is a annual conference held in Region 3 and covers a Professional Track, Student Track and Regional Track.

  • SoutheastCon 2017

    Broad scope professional paper conference, region 3 annual meeting, region 3 annual student conference

  • SoutheastCon 2016

    Annual Region 3 Trifecta of Student competitions, Technical papers and volunteer training and administration.

  • SoutheastCon 2015

    Horizontal Technical Conference with all topics; students compete in multiple competions; Region 3 training meetings.

  • SOUTHEASTCON 2014

    Horizontal Technical Conference with all topics; students compete in multiple competions; Region 3 training meetings.

  • IEEE SOUTHEASTCON 2013

    Region 3 Meeting, Technical papers, student competitions.

  • SOUTHEASTCON 2012

    The annual IEEE SoutheastCon conferences promote all aspects of the theories and applications of the engineering disciplines. Sponsored by the IEEE Region 03, this event attracts researchers, professionals, and students from the Southeast region of the U.S and beyond. SoutheastCon 2012 will be held in Orlando, Florida.

  • SOUTHEASTCON 2011

    IEEE SoutheastCon2011 is the annual IEEE Region 3 technical, professional, and student conference, invites conference refereed and non-refereed technical paper presentations and tutorials that advance the work and careers of conference attendees in the areas of interest for the conference.

  • SOUTHEASTCON 2010

    SoutheastCon 2010 is the Region 3 event which includes a student conference, a technical conference, and the Region 3 business meeting.

  • SOUTHEASTCON 2009

    It is the annual IEEE Region 3 Technical, Professional, and Student Conference. As the premier conference for the IEEE Region 3, it brings together electrical, computer and other engineering and science professionals, faculty and students to share the latest information through technical sessions, tutorials and exhibits. The conference schedule includes: a technical program with seminars, tutorials, and workshops; exhibits; a student program with student competitions; and IEEE regional meetings.

  • SOUTHEASTCON 2008

    SoutheastCon is the Southeastern USA Region of the IEEE's premier conference. It contains three main sections: a technical program, student competitions and regional meetings. SouthEastCon features technical papers, tutorials and exhibits.

  • SOUTHEASTCON 2007

  • SOUTHEASTCON 2006

  • SOUTHEASTCON 2005

  • SOUTHEASTCON 2004

  • SOUTHEASTCON 2003

  • SOUTHEASTCON 2002

  • SOUTHEASTCON 2001

  • SOUTHEASTCON 2000

  • SOUTHEASTCON '99

  • SOUTHEASTCON '98

  • SOUTHEASTCON '97

  • SOUTHEASTCON '96


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Periodicals related to Algorithmic Game Theory

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Automatic Control, IEEE Transactions on

The theory, design and application of Control Systems. It shall encompass components, and the integration of these components, as are necessary for the construction of such systems. The word `systems' as used herein shall be interpreted to include physical, biological, organizational and other entities and combinations thereof, which can be represented through a mathematical symbolism. The Field of Interest: shall ...


Communications, IEEE Transactions on

Telephone, telegraphy, facsimile, and point-to-point television, by electromagnetic propagation, including radio; wire; aerial, underground, coaxial, and submarine cables; waveguides, communication satellites, and lasers; in marine, aeronautical, space and fixed station services; repeaters, radio relaying, signal storage, and regeneration; telecommunication error detection and correction; multiplexing and carrier techniques; communication switching systems; data communications; and communication theory. In addition to the above, ...


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


Computer

Computer, the flagship publication of the IEEE Computer Society, publishes peer-reviewed technical content that covers all aspects of computer science, computer engineering, technology, and applications. Computer is a resource that practitioners, researchers, and managers can rely on to provide timely information about current research developments, trends, best practices, and changes in the profession.


Computers, IEEE Transactions on

Design and analysis of algorithms, computer systems, and digital networks; methods for specifying, measuring, and modeling the performance of computers and computer systems; design of computer components, such as arithmetic units, data storage devices, and interface devices; design of reliable and testable digital devices and systems; computer networks and distributed computer systems; new computer organizations and architectures; applications of VLSI ...


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Most published Xplore authors for Algorithmic Game Theory

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Xplore Articles related to Algorithmic Game Theory

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Securing Majority-Attack in Blockchain Using Machine Learning and Algorithmic Game Theory: A Proof of Work

2018 10th Computer Science and Electronic Engineering (CEEC), 2018

Recently we could see several institutions coming together to create consortium based blockchain networks such as Hyperledger. Although for applications of blockchain such as Bitcoin, Litcoin, etc. the majority-attack might not be a great threat but for consortium based blockchain networks where we could see several institutions such as public, private, government, etc. are collaborating, the majority-attack might just prove ...


An Algorithmic Game-Theory Approach for Coarse-Grain Prediction of RNA 3D Structure

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2013

We present a new approach for the prediction of the coarse-grain 3D structure of RNA molecules. We model a molecule as being made of helices and junctions. Those junctions are classified into topological families that determine their preferred 3D shapes. All the parts of the molecule are then allowed to establish long-distance contacts that induce a 3D folding of the ...


Algorithmic and evolutionary game theory and their applications in Internet of Things

2013 15th International Conference on Advanced Communications Technology (ICACT), 2013

Algorithmic game theory concerns algorithms and their analyses of finding equilibria in multi-agent strategic environments. Nash has shown that, in his seminal work, there is always an equilibrium where all agents can stay with their best responses. Evolutionary game theory concerns on stability and dynamics of agent population through differential reproduction governed by mutation and natural selection. Recently we have ...


Algorithmic Game Theory and Applications

Handbook of Applied Algorithms: Solving Scientific, Engineering, and Practical Problems, None

Methods from game theory and mechanism design have been proven to be a powerful mathematical tool in order to understand, control, and efficiently design dynamic, complex networks, such as the Internet. Game theory provides a good starting point for computer scientists to understand selfish rational behavior of complex networks with many agents. Such a scenario is readily modeled using game ...


Recovery of two process deadlock using payoff matrix approach

2010 3rd International Conference on Computer Science and Information Technology, 2010

In multiprogramming environment, where two processes may compete for a finite number of instances of the same resource type, occurrence of deadlock between them is very usual situation. Key task is to get the appropriate recovery from deadlock such that every process get fair result and resources must not preempted from same process every time. This paper proposes a payoff ...


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Educational Resources on Algorithmic Game Theory

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IEEE-USA E-Books

  • Securing Majority-Attack in Blockchain Using Machine Learning and Algorithmic Game Theory: A Proof of Work

    Recently we could see several institutions coming together to create consortium based blockchain networks such as Hyperledger. Although for applications of blockchain such as Bitcoin, Litcoin, etc. the majority-attack might not be a great threat but for consortium based blockchain networks where we could see several institutions such as public, private, government, etc. are collaborating, the majority-attack might just prove to be a prevalent threat if collusion among these institutions takes place. This paper proposes a methodology where we can use intelligent software agents to monitor the activity of stakeholders in the blockchain networks to detect anomaly such as collusion, using supervised machine learning algorithm and algorithmic game theory and stop the majority-attack from taking place.

  • An Algorithmic Game-Theory Approach for Coarse-Grain Prediction of RNA 3D Structure

    We present a new approach for the prediction of the coarse-grain 3D structure of RNA molecules. We model a molecule as being made of helices and junctions. Those junctions are classified into topological families that determine their preferred 3D shapes. All the parts of the molecule are then allowed to establish long-distance contacts that induce a 3D folding of the molecule. An algorithm relying on game theory is proposed to discover such long-distance contacts that allow the molecule to reach a Nash equilibrium. As reported by our experiments, this approach allows one to predict the global shape of large molecules of several hundreds of nucleotides that are out of reach of the state-of-the-art methods.

  • Algorithmic and evolutionary game theory and their applications in Internet of Things

    Algorithmic game theory concerns algorithms and their analyses of finding equilibria in multi-agent strategic environments. Nash has shown that, in his seminal work, there is always an equilibrium where all agents can stay with their best responses. Evolutionary game theory concerns on stability and dynamics of agent population through differential reproduction governed by mutation and natural selection. Recently we have seen huge potentials of applying research achievements of algorithmic and evolutionary game theories to the domain of Internet of Things, which constitutes an intelligent network of humans, things and services.

  • Algorithmic Game Theory and Applications

    Methods from game theory and mechanism design have been proven to be a powerful mathematical tool in order to understand, control, and efficiently design dynamic, complex networks, such as the Internet. Game theory provides a good starting point for computer scientists to understand selfish rational behavior of complex networks with many agents. Such a scenario is readily modeled using game theory techniques, in which players with potentially different goals participate under a common setting with well prescribed interactions. The Nash equilibrium stands out as the predominant concept of rationality in noncooperative settings. Thus, game theory and its notions of equilibria provide a rich framework for modeling the behavior of selfish agents in these kinds of distributed and networked environments and offering mechanisms to achieve efficient and desirable global outcomes despite selfish behavior. The most important algorithmic solutions and advances achieved through game theory are reviewed.

  • Recovery of two process deadlock using payoff matrix approach

    In multiprogramming environment, where two processes may compete for a finite number of instances of the same resource type, occurrence of deadlock between them is very usual situation. Key task is to get the appropriate recovery from deadlock such that every process get fair result and resources must not preempted from same process every time. This paper proposes a payoff matrix approach that resolve these bottleneck. Proposed algorithm can efficiently find an algorithm for deadlock recovery. In this paper two player zero sum game is played using mixed strategy mechanism, a probabilistic approach where two process are acting as players and environment is fair. The time complexity of proposed algorithm for recovering two process deadlock which hold the instances of same resource type is constant to recover from the deadlock.

  • Price-based Resource Allocation for Edge Computing: A Market Equilibrium Approach

    The emerging edge computing paradigm promises to deliver superior user experience and enable a wide range of Internet of Things (IoT) applications. In this paper, we propose a new market-based framework for efficiently allocating resources of heterogeneous capacity-limited edge nodes (EN) to multiple competing services at the network edge. By properly pricing the geographically distributed ENs, the proposed framework generates a market equilibrium (ME) solution that not only maximizes the edge computing resource utilization but also allocates optimal resource bundles to the services given their budget constraints. When the utility of a service is defined as the maximum revenue that the service can achieve from its resource allotment, the equilibrium can be computed centrally by solving the Eisenberg-Gale (EG) convex program. We further show that the equilibrium allocation is Pareto- optimal and satisfies desired fairness properties including sharing incentive, proportionality, and envy-freeness. Also, two distributed algorithms are introduced, which efficiently converge to an ME. When each service aims to maximize its net profit (i.e., revenue minus cost) instead of the revenue, we derive a novel convex optimization problem and rigorously prove that its solution is exactly an ME. Extensive numerical results are presented to validate the effectiveness of the proposed techniques.

  • Bayesian Mechanism Design

    Systems wherein strategic agents compete for limited resources are ubiquitous. For example, the economy, computer networks, social networks, congestion networks, nature, and so on. Assuming the agents' preferences are drawn from a distribution, a reasonable assumption for small mechanisms in a large system, Bayesian mechanism design governs the design and analysis of these systems. This monograph surveys the classical economic theory of Bayesian mechanism design and recent advances from the perspective of algorithms and approximation. Classical economics gives simple characterizations of Bayes- Nash equilibrium and optimal mechanisms when the agents' preferences are linear and single-dimensional. The mechanisms it predicts are often complex and overly dependent on details of the model. Approximation complements this theory and suggests that simple and less-detail-dependent mechanisms can be nearly optimal. Furthermore, techniques from approximation and algorithms can describe good mechanisms beyond the single-dimensional, linear model of agent preferences. This text is an ideal reference for researchers and students working in the area as it presents over a decade of recent work on algorithmic aspects of mechanism design in the context of the classical economic theory of Bayesian mechanism design.

  • A simulation framework for analyzing complex infinitely repeated games

    We discuss a technique to analyze complex infinitely repeated games using techniques from the fields of game theory and simulations. Our research is motivated by the analysis of electronic markets with thousands of participants and possibly complex strategic behavior. We consider an example of a global market of composed IT services to demonstrate the use of our simulation technique. We present our current work in this area and we want to discuss further approaches for the future.

  • Reducibility among Fractional Stability Problems

    In a landmark paper, Papadimitriou introduced a number of syntactic subclasses of TFNP based on proof styles that (unlike TFNP) admit complete problems. A recent series of results has shown that finding Nash equilibria is complete for PPAD, a particularly notable subclass of TFNP. A major goal of this work is to expand the universe of known PPAD-complete problems. We resolve the computational complexity of a number of outstanding open problems with practical applications. Here is the list of problems we show to be PPAD- complete, along with the domains of practical significance: Fractional Stable Paths Problem (FSPP) - Internet routing; Core of Balanced Games - Economics and Game theory; Scarf's Lemma - Combinatorics; Hypergraph Matching - Social Choice and Preference Systems; Fractional Bounded Budget Connection Games (FBBC) - Social networks; and Strong Fractional Kernel - Graph Theory. In fact, we show that no fully polynomial-time approximation schemes exist (unless PPAD is in FP). This paper is entirely a series of reductions that build in nontrivial ways on the framework established in previous work. In the course of deriving these reductions, we created two new concepts - preference games and personalized equilibria. The entire set of new reductions can be presented as a lattice with the above problems sandwiched between preference games (at the "easy" end) and personalized equilibria (at the "hard" end). Our completeness results extend to natural approximate versions of most of these problems. On a technical note, we wish to highlight our novel "continuous-to- discrete" reduction from exact personalized equilibria to approximate personalized equilibria using a linear program augmented with an exponential number of "min" constraints of a specific form. In addition to enhancing our repertoire of PPAD-complete problems, we expect the concepts and techniques in this paper to find future use in algorithmic game theory.

  • An Incentive-Compatible Routing Protocol for Two-Hop Delay-Tolerant Networks

    Delay-tolerant networks (DTNs) rely on the mobility of nodes and their contacts to make up with the lack of continuous connectivity and, thus, enable message delivery from source to destination in a “store-carry-forward” fashion. Since message delivery consumes resource such as storage and power, some nodes may choose not to forward or carry others' messages while relying on others to deliver their locally generated messages. These kinds of selfish behaviors may hinder effective communications over DTNs. In this paper, we present an efficient incentive-compatible (IC) routing protocol (ICRP) with multiple copies for two-hop DTNs based on the algorithmic game theory. It takes both the encounter probability and transmission cost into consideration to deal with the misbehaviors of selfish nodes. Moreover, we employ the optimal sequential stopping rule and Vickrey-Clarke-Groves (VCG) auction as a strategy to select optimal relay nodes to ensure that nodes that honestly report their encounter probability and transmission cost can maximize their rewards. We attempt to find the optimal stopping time threshold adaptively based on realistic probability model and propose an algorithm to calculate the threshold. Based on this threshold, we propose a new method to select relay nodes for multicopy transmissions. To ensure that the selected relay nodes can receive their rewards securely, we develop a signature scheme based on a bilinear map to prevent the malicious nodes from tampering. Through simulations, we demonstrate that ICRP can effectively stimulate nodes to forward/carry messages and achieve higher packet delivery ratio with lower transmission cost.



Standards related to Algorithmic Game Theory

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